#merged mouse oligodendrocyte scRNA-seq object
#Subset only healthy Oligodendrocytes
#batch effect correctio
#this script focus on applying SCTransform integration pipeline implemented in Seurat R package
#until UMAP embedding

#run under sc_env

#for scRNA-seq objects
library(Seurat)
library(dplyr)
library(Matrix)
library(abind)
library(sctransform)

#for parallelization
library(future)
library(future.apply)

#for visualization
library(cowplot)
library(ggplot2)

#for DGE analysis
library(DESeq2)
library(MAST)
library(patchwork)
library(pheatmap)



#normally unnecessary, for loading sparse matrix
#library(DropSeq.util)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following object is masked from ‘package:Matrix’:

    which

The following objects are masked from ‘package:dplyr’:

    combine, intersect, setdiff, union

The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min


Attaching package: ‘S4Vectors’

The following object is masked from ‘package:future’:

    values

The following object is masked from ‘package:Matrix’:

    expand

The following objects are masked from ‘package:dplyr’:

    first, rename

The following object is masked from ‘package:base’:

    expand.grid

Loading required package: IRanges

Attaching package: ‘IRanges’

The following objects are masked from ‘package:dplyr’:

    collapse, desc, slice

Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: DelayedArray
Loading required package: matrixStats

Attaching package: ‘matrixStats’

The following objects are masked from ‘package:Biobase’:

    anyMissing, rowMedians

The following object is masked from ‘package:dplyr’:

    count

Loading required package: BiocParallel

Attaching package: ‘DelayedArray’

The following objects are masked from ‘package:matrixStats’:

    colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges

The following objects are masked from ‘package:base’:

    aperm, apply, rowsum


Attaching package: ‘SummarizedExperiment’

The following object is masked from ‘package:Seurat’:

    Assays


Attaching package: ‘DESeq2’

The following object is masked from ‘package:sctransform’:

    vst

Loading required package: SingleCellExperiment

Attaching package: ‘patchwork’

The following object is masked from ‘package:cowplot’:

    align_plots

#read in original data (8 differnt mouse single-cell studies, only healthy oligodendroglia profiles)
seu<-readRDS(".../2020_scRNA_mouse_Oligo_merged_UMAPembedded.rds")

seu

An object of class Seurat 
51257 features across 123535 samples within 2 assays 
Active assay: RNA (49257 features, 5000 variable features)
 1 other assay present: integrated
 2 dimensional reductions calculated: pca, umap

table(seu@meta.data$Condition)
table(seu@meta.data$Study,seu@meta.data$Condition)
table(seu@meta.data$Study,seu@meta.data$Age)

        Acute         Aging           CFA          Ctrl    Ctrl_5xFAD 
          532          8996           547         98021          3361 
          EAE         Naive       Priming     Remitting       Trem2KO 
          707          1373           283          1464          4294 
Trem2KO_5xFAD 
         3957

               
                Acute Aging   CFA  Ctrl Ctrl_5xFAD   EAE Naive Priming
  Falcao2018        0     0     0   745          0   707     0       0
  Marques2016       0     0     0  5069          0     0     0       0
  Saunders2018      0     0     0 49270          0     0     0       0
  Wheeler2020     532     0   547     0          0     0  1373     283
  Ximerakis2019     0  8996     0  6404          0     0     0       0
  Zeisel2018        0     0     0 31073          0     0     0       0
  Zeisle2015        0     0     0   820          0     0     0       0
  Zhou2020          0     0     0  4640       3361     0     0       0
               
                Remitting Trem2KO Trem2KO_5xFAD
  Falcao2018            0       0             0
  Marques2016           0       0             0
  Saunders2018          0       0             0
  Wheeler2020        1464       0             0
  Ximerakis2019         0       0             0
  Zeisel2018            0       0             0
  Zeisle2015            0       0             0
  Zhou2020              0    4294          3957

               
                 2-3m 21-22m    7m p12, p35   p16 p16, p24   p18   p19   p20
  Falcao2018        0      0     0        0     0        0     0     0     0
  Marques2016       0      0     0        0     7        0    46   334   416
  Saunders2018      0      0     0        0     0        0     0     0     0
  Wheeler2020       0      0     0        0     0        0     0     0     0
  Ximerakis2019  6404   8996     0        0     0        0     0     0     0
  Zeisel2018        0      0     0       41     0       49     0  3049  4496
  Zeisle2015        0      0     0        0     0        0     0     0    62
  Zhou2020          0      0 16252        0     0        0     0     0     0
               
                  p21 p21-23   p22 p22-24   p23   p24   p25 p25-27   p26   p27
  Falcao2018        0      0     0      0     0     0     0      0     0     0
  Marques2016     561      0   626      0   246   470   278      0   319   273
  Saunders2018      0      0     0      0     0     0     0      0     0     0
  Wheeler2020       0      0     0      0     0     0     0      0     0     0
  Ximerakis2019     0      0     0      0     0     0     0      0     0     0
  Zeisel2018     3904   3768  5508     17   701  1322   696   5293   444   204
  Zeisle2015       29      0    95      0   113   120     5      0   158    94
  Zhou2020          0      0     0      0     0     0     0      0     0     0
               
                  p28   p29   p30   p31   p50   p60   P60   p61   p62   p63
  Falcao2018        0     0     0     0     0     0     0     0     0     0
  Marques2016     230    80     0    11    16   119     0   227   142    20
  Saunders2018      0     0     0     0     0     0 49270     0     0     0
  Wheeler2020       0     0     0     0     0     0     0     0     0     0
  Ximerakis2019     0     0     0     0     0     0     0     0     0     0
  Zeisel2018      317  1225    21     0     0    18     0     0     0     0
  Zeisle2015      118     0     0    26     0     0     0     0     0     0
  Zhou2020          0     0     0     0     0     0     0     0     0     0
               
                  p67   p68   p69 p70-p91   p90
  Falcao2018        0     0     0    1452     0
  Marques2016       2    11    18       0    16
  Saunders2018      0     0     0       0     0
  Wheeler2020       0     0     0       0     0
  Ximerakis2019     0     0     0       0     0
  Zeisel2018        0     0     0       0     0
  Zeisle2015        0     0     0       0     0
  Zhou2020          0     0     0       0     0

#tag all Ximerakis cells with Ctrl or aging
head(seu@meta.data)

seu@meta.data$Condition[which(seu@meta.data$Age == "2-3m")]<-"Ctrl"
seu@meta.data$Condition[which(seu@meta.data$Age == "21-22m")]<-"Aging"
seu@meta.data$Condition[which(seu@meta.data$Condition == "Naive")]<-"Ctrl"

table(seu@meta.data$Study,seu@meta.data$Condition)

               
                Acute Aging   CFA  Ctrl Ctrl_5xFAD   EAE Priming Remitting
  Falcao2018        0     0     0   745          0   707       0         0
  Marques2016       0     0     0  5069          0     0       0         0
  Saunders2018      0     0     0 49270          0     0       0         0
  Wheeler2020     532     0   547  1373          0     0     283      1464
  Ximerakis2019     0  8996     0  6404          0     0       0         0
  Zeisel2018        0     0     0 31073          0     0       0         0
  Zeisle2015        0     0     0   820          0     0       0         0
  Zhou2020          0     0     0  4640       3361     0       0         0
               
                Trem2KO Trem2KO_5xFAD
  Falcao2018          0             0
  Marques2016         0             0
  Saunders2018        0             0
  Wheeler2020         0             0
  Ximerakis2019       0             0
  Zeisel2018          0             0
  Zeisle2015          0             0
  Zhou2020         4294          3957

#update object
#saveRDS(seu,"/media/tsun/Data/Tsun/Ting/DAO_paper/rds/2020_scRNA_mouse_Oligo_merged_UMAPembedded.rds")

#################critical change
#subset healthy Oligodendrocytes
seu<-subset(seu, subset = Condition %in% c("Ctrl","Aging"))

seu

An object of class Seurat 
51257 features across 108390 samples within 2 assays 
Active assay: RNA (49257 features, 5000 variable features)
 1 other assay present: integrated
 2 dimensional reductions calculated: pca, umap

table(seu@meta.data$Condition)
table(seu@meta.data$Study)

Aging  Ctrl 
 8996 99394

   Falcao2018   Marques2016  Saunders2018   Wheeler2020 Ximerakis2019 
          745          5069         49270          1373         15400 
   Zeisel2018    Zeisle2015      Zhou2020 
        31073           820          4640

#batch effect is strongly introduced by different studies

seu.list<-SplitObject(seu, split.by = "Study")

for (i in c(1:length(seu.list))) {
    seu.list[[i]] <- SCTransform(seu.list[[i]], verbose = TRUE)
}

Calculating cell attributes from input UMI matrix: log_umi
Variance stabilizing transformation of count matrix of size 17063 by 5069
Model formula is y ~ log_umi
Get Negative Binomial regression parameters per gene
Using 2000 genes, 5069 cells

  |                                                                      |   0%

Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in sqrt(1/i):
“NaNs produced”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”

  |==================                                                    |  25%

Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”

  |===================================                                   |  50%

Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”

  |====================================================                  |  75%

Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”Warning message in theta.ml(y = y, mu = fit$fitted):
“iteration limit reached”

  |======================================================================| 100%

seu.list

$Marques2016
An object of class Seurat 
68320 features across 5069 samples within 3 assays 
Active assay: SCT (17063 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

$Saunders2018
An object of class Seurat 
70347 features across 49270 samples within 3 assays 
Active assay: SCT (19090 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

$Wheeler2020
An object of class Seurat 
62823 features across 1373 samples within 3 assays 
Active assay: SCT (11566 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

$Ximerakis2019
An object of class Seurat 
65187 features across 15400 samples within 3 assays 
Active assay: SCT (13930 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

$Zeisel2018
An object of class Seurat 
67917 features across 31073 samples within 3 assays 
Active assay: SCT (16660 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

$Falcao2018
An object of class Seurat 
65848 features across 745 samples within 3 assays 
Active assay: SCT (14591 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

$Zeisle2015
An object of class Seurat 
65608 features across 820 samples within 3 assays 
Active assay: SCT (14351 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

$Zhou2020
An object of class Seurat 
66051 features across 4640 samples within 3 assays 
Active assay: SCT (14794 features, 3000 variable features)
 2 other assays present: RNA, integrated
 2 dimensional reductions calculated: pca, umap

seu.features <- SelectIntegrationFeatures(object.list = seu.list, nfeatures = 3000)
seu.list <- PrepSCTIntegration(object.list = seu.list, anchor.features = seu.features)

seu.anchors <- FindIntegrationAnchors(object.list = seu.list, normalization.method = "SCT", 
                                        anchor.features = seu.features)

Finding all pairwise anchors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 17026 anchors
Filtering anchors
	Retained 6705 anchors
Extracting within-dataset neighbors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 14221 anchors
Filtering anchors
	Retained 7075 anchors
Extracting within-dataset neighbors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 48111 anchors
Filtering anchors
	Retained 20351 anchors
Extracting within-dataset neighbors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 17471 anchors
Filtering anchors
	Retained 9004 anchors
Extracting within-dataset neighbors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 62991 anchors
Filtering anchors
	Retained 22048 anchors
Extracting within-dataset neighbors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 35412 anchors
Filtering anchors
	Retained 12835 anchors
Extracting within-dataset neighbors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 3531 anchors
Filtering anchors
	Retained 2912 anchors
Extracting within-dataset neighbors
Running CCA
Merging objects
Finding neighborhoods
Finding anchors
	Found 3659 anchors
Filtering anchors
	Retained 2846 anchors
Extracting within-dataset neighbors

seu.integrated <- IntegrateData(anchorset = seu.anchors, normalization.method = "SCT")

Merging dataset 7 into 3
Extracting anchors for merged samples
Finding integration vectors
Finding integration vector weights
Integrating data
Merging dataset 4 into 3 7
Extracting anchors for merged samples
Finding integration vectors
Finding integration vector weights
Integrating data
Merging dataset 1 into 2
Extracting anchors for merged samples
Finding integration vectors
Finding integration vector weights
Integrating data
Merging dataset 5 into 3 7 4
Extracting anchors for merged samples
Finding integration vectors
Finding integration vector weights
Integrating data
Merging dataset 8 into 6
Extracting anchors for merged samples
Finding integration vectors
Finding integration vector weights
Integrating data
Merging dataset 6 8 into 3 7 4 5
Extracting anchors for merged samples
Finding integration vectors
Finding integration vector weights
Integrating data
Merging dataset 2 1 into 3 7 4 5 6 8
Extracting anchors for merged samples
Finding integration vectors
Finding integration vector weights
Integrating data

seu.integrated <- RunPCA(object = seu.integrated, verbose = FALSE)
ElbowPlot(seu.integrated, ndims = 50)

seu.integrated <- RunUMAP(object = seu.integrated, dims = 1:30)

seu<-seu.integrated

#check for correction
DimPlot(seu, reduction = "umap", group.by = "Study")
DimPlot(seu, reduction = "umap", group.by = "CellType")
DimPlot(seu, reduction = "umap", group.by = "Tissue")
DimPlot(seu, reduction = "umap", group.by = "Platform")
DimPlot(seu, reduction = "umap", group.by = "Age")
DimPlot(seu, reduction = "umap", group.by = "CellTypeOriginal")
DimPlot(seu, reduction = "umap", group.by = "Condition")

#final check for object information
seu

An object of class Seurat 
78467 features across 123535 samples within 3 assays 
Active assay: integrated (3000 features)
 2 other assays present: RNA, SCT
 2 dimensional reductions calculated: pca, umap

	orig.ident	nCount_RNA	nFeature_RNA	CellType	percent.mt	sample_ID	Strain	Tissue	Sex	Age	CellTypeOriginal	CellTypeSubcluster	Study	Platform	Condition	SampleID	Genotype	ConditionOriginal
1771017030_C09	Goncalo_2016	4202	1406	OPC	0.1665873	1771017030_C09	PDGFRA-GFP	CortexS1	1	p22	Marques_OPC	Marques_OPC	Marques2016	Smart-Seq2	Ctrl	NA	NA	NA
1771017028_G05	Goncalo_2016	2913	1245	OPC	0.4119464	1771017028_G05	PDGFRA-GFP	HippocampusCA1	1	p22	Marques_OPC	Marques_OPC	Marques2016	Smart-Seq2	Ctrl	NA	NA	NA
1771052132_B02	Goncalo_2016	3826	1834	OPC	0.4181913	1771052132_B02	CD-1	CorpusCallosum	-1	p69	Marques_OPC	Marques_OPC	Marques2016	Smart-Seq2	Ctrl	NA	NA	NA
1772099214_D12	Goncalo_2016	2673	1264	OPC	0.2618780	1772099214_D12	CD-1	DentateGyrus	-1	p63	Marques_OPC	Marques_OPC	Marques2016	Smart-Seq2	Ctrl	NA	NA	NA
1771017029_D09	Goncalo_2016	2726	1221	OPC	0.4402054	1771017029_D09	PDGFRA-GFP	HippocampusCA1	1	p22	Marques_OPC	Marques_OPC	Marques2016	Smart-Seq2	Ctrl	NA	NA	NA
1772099314_B05	Goncalo_2016	6712	2641	OPC	0.5214541	1772099314_B05	C57BL6	DorsalHorn	1	p22	Marques_OPC	Marques_OPC	Marques2016	Smart-Seq2	Ctrl	NA	NA	NA